Why is it recommended against using a dynamic start_date in Airflow?

Question

I've read Airflow's FAQ about "What's the deal with start_date?", but it still isn't clear to me why it is recommended against using dynamic start_date.

To my understanding, a DAG's execution_date is determined by the minimum start_date between all of the DAG's tasks, and subsequent DAG Runs are ran at the latest execution_date + schedule_interval.

If I set my DAG's default_args start_date to be for, say, yesterday at 20:00:00, with a schedule_interval of 1 day, how would that break or confuse the scheduler, if at all? If I understand correctly, the scheduler would trigger the DAG with an execution_date of yesterday at 20:00:00, and the next DAG Run would be scheduled for today at 20:00:00.

Is there some concept that I'm missing?

Answer 1

First run would be at start_date+schedule_interval. It doesn't run dag on start_date, it always runs on start_date+schedule_interval.

As they mentioned in document if you give start_date dynamic for e.g. datetime.now() and give some schedule_interval(1 hour), it will never execute that run as now() moves along with time and datetime.now()+ 1 hour is not possible